Calculate the VAR model and apply restrictions

This function calls the vars::var function to calculate the VAR model and applies restrictions if needed. We set the intercept to 1 for restricted equations because calculations go wrong otherwise (this is a bug in the vars library).

run_var(endo_matrix, exo_matrix, lag)

Arguments

endo_matrix	A numeric matrix of endogenous data.
exo_matrix	Either NULL or a numeric matrix of exogenous data.
lag	A nonnegative integer specifying the lag length of the model. Specifying 0 for the lag results in calculating a lag 1 model with all lag-1 terms restricted.

Value

A varest object with the VAR estimation result.

Examples

endo_matrix <- matrix(rnorm(120), ncol = 2, nrow = 60,
                      dimnames = list(NULL, c("rumination", "activity")))
autovarCore:::run_var(endo_matrix, NULL, 1)
#> 
#> VAR Estimation Results:
#> ======================= 
#> 
#> Estimated coefficients for equation rumination: 
#> =============================================== 
#> Call:
#> rumination = rumination.l1 + activity.l1 + const 
#> 
#> rumination.l1   activity.l1         const 
#>     0.2228954     0.1306920    -0.0332642 
#> 
#> 
#> Estimated coefficients for equation activity: 
#> ============================================= 
#> Call:
#> activity = rumination.l1 + activity.l1 + const 
#> 
#> rumination.l1   activity.l1         const 
#>   -0.06740661   -0.22231376    0.10066133 
#> 
#>